A dynamic Markov regime-switching asymmetric GARCH model and its cumulative impulse response function. (English. French summary) Zbl 1487.60134
Summary: In this paper, we consider the Markov regime-switching GJR-GARCH(1,1) model to capture both the cumulative impulse response and the asymmetry of the dynamic behavior of financial market volatility in stationary and explosive states. The model can capture regime shifts in volatility between two regimes as well as the asymmetric response to negative and positive shocks. A Monte Carlo simulation is conducted to validate the main theory and find that the regime-switching GJR-GARCH model performs better than the standard GJR-GARCH model. Applications to Brazilian stock market data show that the proposed model performs well in terms of cumulative impulse response.
MSC:
| 60J10 | Markov chains (discrete-time Markov processes on discrete state spaces) |
| 62M20 | Inference from stochastic processes and prediction |
Keywords:
forecasting; GJR-GARCH(1, 1); Markov regime-switching; asymmetry; cumulative impulse responseReferences:
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